ModelRefs / DeepSeek R1 vs Llama 4 Scout — Benchmarks, Pricing & Coding…
DeepSeek R1 vs Llama 4 Scout — Benchmarks, Pricing & Coding…
DeepSeek R1 vs Llama 4 Scout: side-by-side benchmarks, pricing, context windows, coding ability and deployment. Pick the right model for your stack.
Overview
DeepSeek R1: DeepSeek R1 is DeepSeek's open-source reasoning model, trained with reinforcement learning to produce chain-of-thought reasoning before answering. Released in January 2025 under the MIT license, it matched or exceeded closed reasoning models on several math and coding benchmarks.
Llama 4 Scout: Llama 4 Scout is Meta's efficiency-focused open-weights model with an exceptionally large 10M-token context window and vision support. It is optimized for long-document retrieval and low-cost inference at scale.
Context window: DeepSeek R1 accepts up to 128,000 tokens, Llama 4 Scout up to 10,000,000. Confirm the limit for your specific deployment channel before relying on it.
DeepSeek R1 vs Llama 4 Scout at a glance
| Attribute | DeepSeek R1 | Llama 4 Scout |
|---|---|---|
| Provider | DeepSeek | Meta |
| Released | 2025-01-20 | 2025-04-01 |
| Context window | 128,000 tokens | 10,000,000 tokens |
| Input price | $0.55/M tokens | $0.11/M tokens |
| Output price | $2.19/M tokens | $0.34/M tokens |
| Licence | MIT | Llama 4 Community |
| Self-hostable | Yes, open weights | Yes, open weights |
| Modalities | text | text, vision |
Benchmarks reported for both
| Benchmark | DeepSeek R1 | Llama 4 Scout | Reported |
|---|---|---|---|
| gpqa | 71.5 | 57.2 | 2025-01-20 / 2025-04-01 |
| livecodebench | 65.9 | 32.8 | 2025-04-01 |
Scores are as published by their cited sources on the dates shown. Different runs use different harnesses, prompts, and dates, so treat these as directional evidence rather than a head-to-head result.
Where they differ most
- Coding: DeepSeek R1 66%, Llama 4 Scout 33%. DeepSeek R1 leads on this dimension.
- Cost Efficiency: DeepSeek R1 75%, Llama 4 Scout 94%. Llama 4 Scout leads on this dimension.
- Reasoning: DeepSeek R1 76%, Llama 4 Scout 67%. DeepSeek R1 leads on this dimension.
Capability scores are ModelRefs' own derived signals, not vendor claims or benchmark results. Validate against your own workload before relying on them.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to DeepSeek R1 vs Llama 4 Scout — Benchmarks, Pricing & Coding….
Frequently asked questions
Which is better, DeepSeek R1 or Llama 4 Scout?
DeepSeek R1 and Llama 4 Scout target different workloads — see the benchmark and pricing tables for a side-by-side answer.
Is DeepSeek R1 cheaper than Llama 4 Scout?
Compare $0.00055 vs $0.00011 on this page.